#!/usr/bin/python

# <bitbar.title>Crypto20</bitbar.title>
# <bitbar.version>v1.0</bitbar.version>
# <bitbar.author>Christopher Chen</bitbar.author>
# <bitbar.author.github>cchen408</bitbar.author.github>
# <bitbar.desc>Display Nav and Underlying Asset Information</bitbar.desc>
# <bitbar.image>https://raw.githubusercontent.com/cchen408/bitbar-c20/master/screenshots/chris.png</bitbar.image>
# <bitbar.dependencies>python</bitbar.dependencies>
# <bitbar.abouturl>https://github.com/cchen408/bitbar-c20</bitbar.abouturl>

import json
from urllib import urlopen

# change this to the number of C20 tokens that you own
number_of_c20 = 125438.3242

result = json.loads(urlopen('https://crypto20.com/status').read())
btg_result = json.loads(urlopen('https://api.coinmarketcap.com/v1/ticker/bitcoin-gold/').read())
eth_result = json.loads(urlopen('https://api.coinmarketcap.com/v1/ticker/ethereum').read())
btc_result = json.loads(urlopen('https://api.coinmarketcap.com/v1/ticker/bitcoin').read())
top_25_result = json.loads(urlopen('https://api.coinmarketcap.com/v1/ticker/?limit=25').read())
crypto_global_result = json.loads(urlopen('https://api.coinmarketcap.com/v1/global/').read())

# parse out price and put here
symbol_price = {
    'bitcoin-gold': btg_result[0]['price_usd']
};

# loop through prices rather than call api more than once
for c in top_25_result:
    symbol_price[c['id']] = float(c['price_usd'])

# symbol to name map
symbol_path_map = {
    'BTC': 'bitcoin',
    'ETH': 'ethereum',
    'BCH': 'bitcoin-cash',
    'XRP': 'ripple',
    'DASH': 'dash',
    'LTC': 'litecoin',
    'MIOTA': 'iota',
    'XMR': 'monero',
    'NEO': 'neo',
    'XEM': 'nem',
    'ETC': 'ethereum-classic',
    'LSK': 'lisk',
    'QTUM': 'qtum',
    'EOS': 'eos',
    'ZEC': 'zcash',
    'OMG': 'omisego',
    'ADA': 'cardano',
    'HSR': 'hshare',
    'XLM': 'stellar',
    'WAVES': 'waves',
    'PPT': 'populous',
    'STRAT': 'stratis',
    'BTS': 'bitshares',
    'ARK': 'ark',
    'BTG': 'bitcoin-gold'
}

# symbol to icon map
# To generate the images, grab the image (PNG) and increase the DPI from 72 to
# 144. Then resize the image to 32x32. Finally encode the image into base 64.
# i.e. base64 --input bitcoin.png
# Then add the resulting encoded text to the correct map entry below.
symbol_image_map = {
    'C20': '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',
    'BTC': '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',
    'ETH': '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',
    'BCH': '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',
    'XRP': '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',
    'DASH': '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',
    'LTC': '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',
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    'QTUM': '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',
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    'ZEC': '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',
    'OMG': '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',
    'ADA': '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',
    'HSR': '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',
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    'ARK': 'iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAAAXNSR0IArs4c6QAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAACXBIWXMAABYlAAAWJQFJUiTwAAABWWlUWHRYTUw6Y29tLmFkb2JlLnhtcAAAAAAAPHg6eG1wbWV0YSB4bWxuczp4PSJhZG9iZTpuczptZXRhLyIgeDp4bXB0az0iWE1QIENvcmUgNS40LjAiPgogICA8cmRmOlJERiB4bWxuczpyZGY9Imh0dHA6Ly93d3cudzMub3JnLzE5OTkvMDIvMjItcmRmLXN5bnRheC1ucyMiPgogICAgICA8cmRmOkRlc2NyaXB0aW9uIHJkZjphYm91dD0iIgogICAgICAgICAgICB4bWxuczp0aWZmPSJodHRwOi8vbnMuYWRvYmUuY29tL3RpZmYvMS4wLyI+CiAgICAgICAgIDx0aWZmOk9yaWVudGF0aW9uPjE8L3RpZmY6T3JpZW50YXRpb24+CiAgICAgIDwvcmRmOkRlc2NyaXB0aW9uPgogICA8L3JkZjpSREY+CjwveDp4bXBtZXRhPgpMwidZAAAFFUlEQVRYCdWW22/VRRDHZ3d71VrAhAQ11gvIgw/aqiEtKtgAWouS1Bjig5AID7zoA/4BUtAnMTyZKCaYmGhijEoUiloKtJRLjaRSQzQq8qDxhhGxFDm9nB0/8+tZUqWXU2MlbrLn7G92Zr7fmdmd30/k/zxaRbzNyxLDWOCx6/+EjBai3i2yeB/TQJNsugRKpmtQ0AcPFt6/WK3qRLWOx0xW2C/6b9r1OyBS4gB73/unMK6rFKn9TORJk9le0cj/RLG1kPpdIjUQOPNeCPqJc9rn3K/HkJnPpGPrYsa0MnCrCIGKlHr/fLlzc6LIiM0ykaud91ttL+nYupiROSxG0dLbCNgHIbSUqL7b71yEvb82RruH+QqRMKT6yJ0iO5NuMX6LIqBEjqLuEakm0l6inj8IAWQZgSASmT4vcuo0B7JZpD/ZTEWiqBJ0Ep054tRvItL5w2TCwAGBSzb9IDIO5M1z0THdzoKNrScbU2bgLRytJsV7RerV+yM5vFl0eefyAAYrwRD7MAlMtYgo0WJK0ZNsJyMwVQacgePAuRC2kQYjHCEwMgvAYdXXnXNvzGZtMtvjHroR57YZaLK19URjUgIHcGyG+73fWK7acGE09fEqgszF2LYqxjW3xfg48jYIWQ+IplMu0nBY5GmzTT5sPd6YsARE5NmMtNr5dvCoezWpHrpSpCynurdStblxNGrZzs1c5Fwb13HFWXTIF0vph+Qdy0S+Sb7GIzBpBswgOLeViKqpQ65qFPzgz6qrErjpbBAZPouM83HQdEzXbMqwtf3JxrgESJu123gohNU0nJaBUfCKIed6BlRXPsGzOf1U5Ll93j9rawjl+tlj42NKVGE2EGjp4iiYL/Npen8f7P11kK7szneLzGF1nPteY/kk/b0hxmUAkWWR4yLPVDu3+Xu0z4lsao5xi8nNjqztY9ad5zmofntOtfYhkd+Sb9NL45IMdBYOXon3W0oBL0WT430C8AcS+FGRhyG35nd4EHWfU137kckY9wI0qHr/iOoJIw6RmirvN9teZ8G3rccddm9tgxO85DD3/Kj32uXcFx+KXDOuwSRCUj6vG9tufHR4P8JhXmLqCSOZji2BrdUUbnCuu9K5hn6Rr/IxLl8q8p0Z7Be5m0LeRGQXOGSexuN/wYYMKc+RWUmnPLVI5Ijpd4lcT/vsQL5wgPNzJp+/Z0xvoCJjDgaMQyPZrhHZOBvwM6on86pNCXxXCI/y/CbgWZb4CBErD40oE1gtLQJ08j2qj9WLvG22XTE25Zxrr6aTDtFPJMYXEhbqo69XLdx5aC+g7l8i/4kut5RvrZOmtDuEdbNUdyQQIpIyCNjzDxCwAbGMCNdQrmDvD9X1tSKv2h6AC2jdXXTIeTHGhc30hlYwmfZCI38FAnxcdBBeA6/VWiL4Gnl4hb3rQlirqlUA50ixL6X/W/QMd5oaUwrHnpqsBATKVMHzefrBa7wTDCTfLnILDa2Pw3nkQdXlCdPAs/vZK7KeL5vBnuybIiM17r3NYKf5c6CAsQff7d7n+KZYby5MnmXgczvl3F3Svu523mLHaK130d0Sjh3MuYVyJdlU//cRg0We9LbjcwM+IVFPc9sB1vImkR+z/V7vX+LDktKIGHgy+rf/k28y0Mw35cvm35HyFeS6jIjbrBywttfqjA1LeyMY74Swkhs0JEdFbjQ0wC/pijPFImHtLGBnXzgzBTaRX0iQbMbFxUSaMyi/nNgXw/oTI2nUU2lVib8AAAAASUVORK5CYII=',
    'BTG': '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',
    'MARKET': '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'
}

# calculate btg nav
btg_val = int(float(btg_result[0]['price_usd']) * 458)
btg_nav = float(btg_val) / float(result['presale']) * 0.98 * 0.87

# add on top of current nav
net_asset_value = float(result['nav_per_token']) + btg_nav

# calculate the price in eth
eth_price = float(eth_result[0]['price_usd'])
nav_eth = net_asset_value / eth_price

# calculate the price in btc
btc_price = float(btc_result[0]['price_usd'])
nav_btc = net_asset_value / btc_price

# calculate total value
usd_value = net_asset_value * number_of_c20

# menu bar icon
print '${:.4f}| templateImage={}'.format(net_asset_value, symbol_image_map['C20'])
print '---'

# print nav, value of your coins, and total fund value
print 'NAV:\t${:.4f} USD | href=https://crypto20.com/en/portal/performance/ image={}'.format(net_asset_value, symbol_image_map['C20'])

# print nav in ETH and BTC with separator
print 'NAV:\t{:.8f} ETH | href=https://crypto20.com/en/portal/performance/ image={}'.format(nav_eth, symbol_image_map['ETH'])
print 'NAV:\t{:.8f} BTC | href=https://crypto20.com/en/portal/performance/ image={}'.format(nav_btc, symbol_image_map['BTC'])
print '---'

# print number of c20 you have and their value
print 'My Tokens:\t\t{:,.4f} | href=https://crypto20.com/users/ image={}'.format(number_of_c20, symbol_image_map['C20'])
print 'My Value:\t\t${:,.2f} | href=https://crypto20.com/users/ image={}'.format(usd_value, symbol_image_map['C20'])
print '---'

# tokens issues
print 'Tokens Issued:\t{:,} | href=https://crypto20.com/portal/performance/ image={}'.format(int(result['presale']), symbol_image_map['C20'])
print 'Fund Cap:\t\t${:,} | href=https://crypto20.com/portal/insights/ image={}'.format(btg_val + int(result['usd_value']), symbol_image_map['C20'])

# print total crypto market cap
print 'Market Cap:\t\t${:,} | href=https://livecoinwatch.com image={}'.format(int(crypto_global_result['total_market_cap_usd']), symbol_image_map['MARKET'])

# separator bitbar recognizes and puts everything under it into a menu
print '---'

# print holdings
holdings = result['holdings'];
holdings.append({'name': 'BTG', 'value': btg_val})

for holding in holdings:
    crypto_symbol = holding['name']
    crypto_value = float(holding['value'])
    crypto_percentage = crypto_value / float(result['usd_value']) * 100
    c20_value = holding['value']
    crypto_name = symbol_path_map[crypto_symbol]
    crypto_img = symbol_image_map[crypto_symbol]
    crypto_price = float(symbol_price[crypto_name])

    print '{:s} \t{:.2f}%\t${:,}\t${:,.2f} | href=https://coinmarketcap.com/currencies/{:s} image={}'.format(
        crypto_symbol,
        crypto_percentage,
        c20_value,
        crypto_price,
        crypto_name,
        crypto_img)

## Print dashboards
print "---"
print "Dashboards"
print "--youcan.dance/crypto20 | href=http://youcan.dance/crypto20"
print "--cryptodash1.firebaseapp | href=https://cryptodash1.firebaseapp.com/"